Image Super-Resolution Via Sparse Representation

11 years 1 months ago
Image Super-Resolution Via Sparse Representation
This paper presents a new approach to single-image superresolution, based on sparse signal representation. Research on image statistics suggests that image patches can be wellrepresented as a sparse linear combination of elements from an appropriately chosen over-complete dictionary. Inspired by this observation, we seek a sparse representation for each patch of the low-resolution input, and then use the coefficients of this representation to generate the high-resolution output. Theoretical results from compressed sensing suggest that under mild conditions, the sparse representation can be correctly recovered from the downsampled signals. By jointly training two dictionaries for the low- and high-resolution image patches, we can enforce the similarity of sparse representations between the low resolution and high resolution image patch pair with respect to their own dictionaries. Therefore, the sparse representation of a low resolution image patch can be applied with the high resolution...
Jianchao Yang, John Wright, Thomas S. Huang, Yi Ma
Added 22 May 2011
Updated 22 May 2011
Type Journal
Year 2010
Where TIP
Authors Jianchao Yang, John Wright, Thomas S. Huang, Yi Ma
Comments (0)